下面链接的ppt是可以下载的，一些是stata的例子
http://econ.lse.ac.uk/courses/ec220/G/ieppt/series2/

Ec220: Introduction to Econometrics

---

PowerPoint slideshowsThe slideshows can be downloaded by clicking on the title of the slideshow and viewed in Microsoft PowerPoint or PowerPoint Viewer. PowerPoint Viewer can be downloaded from the Microsoft website at http://microsoft.com/downloads/.
If you open a file in Microsoft PowerPoint, you may need to select SlideShow-ViewShow to run it as a slide show presentation. In PowerPoint Viewer, the file will be launched automatically in slide show format. In both cases, press the [F1] key for help in navigating the slide show.

Review Chapter Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7

Chapter 8 Chapter 9 Chapter 10 Chapter 11 Chapter 12 Chapter 13 Chapter 14 Revision Lectures

Review Chapter

• Probability distribution example: X is the sum of two dice [Revision Video]
• Expected value of a random variable [Revision Video]
• Expected value of a function of a random variable [Revision Video]
• Expected value rules [Revision Video]
• Population variance of a discreet random variable [Revision Video]
• Alternative expression for population variance [Revision Video]
• The fixed and random components of a random variable [Revision Video]
• Continuous random variables [Revision Video]
• Independence of two random variables[Revision Video]
• Covariance, covariance and variance rules, and correlation [Revision Video]
• Sampling and estimators [Revision Video]
• Unbiasedness and efficiency [Revision Video]
• Conflicts between unbiasedness and minimum variance [Revision Video]
• Estimators of variance, covariance, and correlation [Revision Video]
• The normal distribution [Revision Video]
• Hypothesis testing [Revision Video]
• Type II error and the power of a test
• t tests [Revision Video]
• Confidence intervals [Revision Video]
• One-sided t tests
• Asymptotic properties of estimators: plims and consistency
• Asymptotic properties of estimators: the use of simulation
• The central limit theorem
• Exercise R.2
• Exercise R.4
• Exercise R.7
• Exercises R.10 and R.12
• Exercise R.13
• Exercise R.19
• Exercise R.22
  

[size=-2]Back to top

Chapter 1

• Simple regression model [Revision Video]
• Deriving linear regression coefficients
• Interpretation of a regression equation [Revision Video]
• Changes in the units of measurement
• Goodness of fit [Revision Video]
• Exercise 1.5
• Exercise 1.7
• Exercise 1.9
• Exercise 1.16 [Revision Video]
  

[size=-2]Back to top

Chapter 2

• Types of regression model and assumptions for Model A [Revision Video]
• Random components, unbiasedness of the regression coefficients [Revision Video]
• A Monte Carlo experiment [Revision Video]
• Precision of the regression coefficients [Revision Video]
• Testing a hypothesis relating to a regression coefficient (2010/2011 version)
  Revision Video Part I | Revision Video Part II
  This slideshow covers the content of the next five slideshows. It takes account of the fact that this year we have covered much of the conceptual content of those slideshows with additional lectures for the Review of Statistics in the first two weeks of term. The five slideshows have been left in place for those who wish to go over all of this material a further time.
  
  • Testing a hypothesis relating to a regression coefficient [Revision Video]
  • Type I error and Type II error [Revision Video]
  • t test of a hypothesis relating to a regression coefficient [Revision Video]
  • Confidence intervals [Revision Video]
  • One-sided t tests [Revision Video]
    
• F test of goodness of fit [Revision Video]
• Exercise 2.11 [Revision Video]
• Exercise 2.16
• Exercise 2.22
• Exercise 2.24
  

[size=-2]Back to top

Chapter 3

• Multiple regression with two explanatory variables: example [Revision Video]
• Graphing a relationship in a multiple regression model [Revision Video]
• Properties of the multiple regression coefficients [Revision Video]
• Precision of the multiple regression coefficients
• Multicollinearity [Revision Video]
• Alleviation of multicollinerarity [Revision Video]
• F tests in a multiple regression model [Revision Video]
• Hedonic pricing
• Prediction
• Exercise 3.5
• Exercise 3.9
  

[size=-2]Back to top

Chapter 4

• Linearity and nonlinearity
• Elasticities and logarithmic models [Revision Video]
• Semilogarithmic models [Revision Video]
• The disturbance term in logarithmic models [Revision Video]
• Comparing linear and logarithmic specifications [Revision Video]
• Quadratic variables and higher-order polynomials
• Interactive explanatory variables [Revision Video]
• Ramsey's RESET test of functional misspecification
• Nonlinear regression [Revision Video]
• Exercise 4.5 [Revision Video]
  

[size=-2]Back to top

Chapter 5Please click on the links below to review the following revision topics. After you have clicked the link, select the "high speed audio" option. These revision topics have audio and powerpoint only

• Dummy variable classification with two categories [Revision Video]
• Dummy classification with more than two categories [Revision Video]
• The effects of changing the reference category [Revision Video]
• Two sets of dummy variables [Revision Video]
• The dummy variable trap [Revision Video]
• Slope dummy variables [Revision Video]
• Chow test [Revision Video]
• Chow test and dummy variable group test [Revision Video]
• Exercise 5.2 [Revision Video]
• Exercise 5.5 [Revision Video]
  

[size=-2]Back to top

Chapter 6

• Variable misspecification I: omitted variable bias [Revision Video]
• Where does the disturbance term end and omitted variable bias
• Variable misspecification II: inclusion of an irrelevant variable [Revision Video]
• Variable misspecification III: consequences for diagnostics [Revision Video]
• Proxy variables [Revision Video]
• F test of a linear restriction [Revision Video]
• Reparameterization of a model and t test of a linear restriction [Revision Video]
• Multiple restrictions and zero restrictions [Revision Video]
• Exercise 6.4
• Exercise 6.7 [Revision Video]
• Exercise 6.13 [Revision Video]
  

[size=-2]Back to top

Chapter 7

• Heteroscedasticity [Revision Video]
• Goldfeld-Quandt test for heteroscedasticity [Revision Video]
• White test for heteroscedasticity [Revision Video]
• Weighted least squares and logarithmic regressions [Revision Video]
• Heteroscedasticity-consistent standard errors
• Heteroscedasticity: Monte Carlo illustration
• Exercise 7.5 [Revision Video]
• Research Assistant Example [Revision Video]
  

[size=-2]Back to top

Chapter 8

• Stochastic regressors and assumptions for Model B [Revision Video]
• Model B: Properties of the regression coefficients [Revision Video]
• Measurement error [Revision Video]
• Friedman's critique of OLS estimation of the consumption function [Revision Video]
• Instrumental variables [Revision Video]
• Asymptotic and finite sample distributions of the IV estimator [Revision Video]
• Durbin-Wu-Hausman specification test [Revision Video]
  

[size=-2]Back to top

Chapter 9

• Simultaneous equations bias [Revision Video]
• Instrumental variable estimation of simultaneous equations [Revision Video]
• Instrumental variable estimation: variation [Revision Video]
• Two-stage least squares [Revision Video]
• Simultaneous equations estimation: Durbin-Wu-Hausman test [Revision Video]
  

[size=-2]Back to top

Chapter 10

• Binary choice: linear probability model [Revision Video]
• Binary choice: logit models [Revision Video]
• Binary choice: probit models [Revision Video]
• Tobit models [Revision Video]
• Sample selection bias [Revision Video]
• Introduction to maximum likelihood estimation [Revision Video]
• Maximum likelihood estimation of regression coefficients [Revision Video]
  

[size=-2]Back to top

Chapter 11

• Model C assumptions [Revision Video]
• Static models and models with lags [Revision Video]
• Models with a lagged dependent variable [Revision Video]
• Partial adjustment model [Revision Video]
• Error correction model
• Adaptive expectations
• Friedman [Revision Video]
• Assumption C.7 [Revision Video]
• Limiting distribution of OLS estimator in univariate process [Revision Video]
• Simultaneous equation models [Revision Video]
• Alternative dynamic representations
  

[size=-2]Back to top

Chapter 12

• Autocorrelation [Revision Video]
• Consequences of autocorrelation
• Testing for autocorrelation
• Eliminating AR(1) autocorrelation [Revision Video]
• Footnote: the Cochrane-Orcutt iterative process [Revision Video]
• Autocorrelation, partial adjustment, and adaptive expectations [Revision Video]
• Housing dynamics [Revision Video]
• Common factor test [Revision Video]
• Dynamic model specification [Revision Video]
• Exercise 12.7 [Revision Video]
  

[size=-2]Back to top

Chapter 13

• Stationary processes [Revision Video] [Revision Video Part II]
• Nonstationary processes [Revision Video]
• Spurious regressions
• Graphical techniques for detecting nonstationarity [Revision Video]
• Tests of nonstationarity: introduction
• Tests of nonstationarity: untrended data
• Tests of nonstationarity: trended data
• Tests of nonstationarity: example and further complications [Revision Video]
• Cointegration [Revision Video]
• Fitting models with nonstationary time series [Revision Video]
  

[size=-2]Back to top

Chapter 14

• Regression analysis with panel data [Revision Video]
• Fixed effects regressions: within-groups and first-differences methods [Revision Video]
• Fixed effects regressions: least square dummy variable apporach [Revision Video]
• Random effects regressions [Revision Video]
• Fixed effects or random effects? [Revision Video]
  

Revision Lectures 2011

• Revision Lecture One (12 May 2011)
• Revision Lecture Two (12 May 2011)
• Revision Lecture Slides:
  
  • Autocorrelation
  • Stationary Processes
  • Dummy Variables
    

Revision Lectures 2010

• Revision Lecture: 27th April 2010 [Recording] [Notes]
• Revision Lecture: 28th April 2010 [Recording] [Notes]
• Revision Lecture: 4th May 2010 [Recording] [Notes]
• Revision Lecture: 7th May 2010 [Recording] [Notes]
• Revision Lecture: 10th May 2010 [Recording] [Notes]
• Revision Lecture: 11th May 2010 [Recording] [Notes]
  

Revision Lectures & Timetable 2009

• Friday 1 May, 1400 - 1600 in room E171 (New Theatre) - Mr Christoph UNGERER - "Omitted Variable Bias, Including Irrelevant Variables and Heteroscedasticity" please prepare Q2 from past exam paper 2005
  
  • Revision Lecture 1 Notes [Revision Lecture]
    
• Thursday 7 May, 1100 - 1300, room E171 - Mr Christoph UNGERER - "Measurement Error & Simulateneous Equations Bias" please prepare Q5 from past exam paper 2005
  
  • Revision Lecture 2 Notes [Revision Lecture]
    
• Friday 8 May, 1400 - 1600, room E171 - Mr Abhisek BANERJEE - "Limited Dependent Variable Models"
  
  • Revision Lecture 3 Notes [Revision Lecture]
    
• Tuesday 12 May, 0900 - 1100, room E171 - Mr Abhisek BANERJEE - "Time Series, Dynamic Models & Autocorrelation"
  
  • Revision Lecture 4 Notes [Revision Lecture]
    
• Tuesday 12 May, 1600 - 1800, room E171, Mr Abhisek BANERJEE - "Nonstationary Time Series"
  
  • Revision Lecture 5 Notes [Revision Lecture]
    

2008 Revision Lectures

• Revision Lecture: 30th April 2008
• Revision Lecture: 7th May 2008
• Revision Lecture: 8th May 2008
• Revision Lecture: 9th May 2008
• Revision Lecture: 13th May 2008
• Revision Lecture: 15th May 2008 (AM)
• Revision Lecture: 15th May 2008 (PM)
  

[size=-2]Back to top

All the slideshows are copyright Christopher Dougherty 1997, 1998, 1999, 2000, all rights reserved, but you may download them freely for personal use.